private void ImportPersonEnter_DragDrop(object sender, DragEventArgs e)
{
if (e.Data.GetDataPresent(DataFormats.FileDrop))
{
string[] files = (string[])e.Data.GetData(DataFormats.FileDrop);
string extenstion = System.IO.Path.GetExtension(files[0]);
if (string.Compare(extenstion, ".jpg", false) == 0)
{
InitCotrol(true);
Image img = Damany.Util.Extensions.MiscHelper.FromFileBuffered(files[0]);
img.Tag = files[0];
this.picTargetPerson.Image = img;
this.InitCotrol(true);
using (var ipl = IplImage.FromFile(files[0]))
{
var facesRect = ipl.LocateFaces(searcher);
if (facesRect.Length > 0)
{
drawRectangle = facesRect[0].ToRectangle();
}
}
}
else if (System.IO.Directory.Exists(files[0]))
{
this.OpenExisted(files[0]);
}
}
}
public IplImage GetIpl()
{
if (_ipl == null)
{
_ipl = IplImage.FromFile(ImageFilePath);
_ipl.ROI = FaceRect;
}
return(_ipl);
}
private static void readImage3()
{
// it uses `System.Drawing.Bitmap` behind the scene.
using (var img = IplImage.FromFile(@"..\..\images\ocv02.jpg", LoadMode.Unchanged))
{
using (var window = new CvWindow("window"))
{
window.Image = img;
Cv.WaitKey();
}
}
}
private void btnOpenMappingImage_Click(object sender, EventArgs e)
{
OpenFileDialog OFD = new OpenFileDialog();
DialogResult Dr = OFD.ShowDialog();
if (Dr == System.Windows.Forms.DialogResult.OK)
{
//ColorImage.SetZero();
mappingimage = IplImage.FromFile(OFD.FileName, LoadMode.AnyColor);
pictureBox1.Image = mappingimage.ToBitmap();
}
}
static void Main(string[] args)
{
//读入源文件
var src = IplImage.FromFile("source.jpg");
//转换到灰度图
var gray = Cv.CreateImage(src.Size, BitDepth.U8, 1);
Cv.CvtColor(src, gray, ColorConversion.BgrToGray);
//做一下膨胀，x与y方向都做，但系数不同
//使用了Erode方法，腐蚀操作，针对白色区域，所以等效于对文字进行了膨胀
var kernal = Cv.CreateStructuringElementEx(5, 2, 1, 1, ElementShape.Rect);
Cv.Erode(gray, gray, kernal, 2);
//二值化
Cv.Threshold(gray, gray, 0, 255, ThresholdType.BinaryInv | ThresholdType.Otsu);
//检测连通域，每一个连通域以一系列的点表示，FindContours方法只能得到第一个域
var storage = Cv.CreateMemStorage();
CvSeq <CvPoint> contour = null;
Cv.FindContours(gray, storage, out contour, CvContour.SizeOf, ContourRetrieval.CComp, ContourChain.ApproxSimple);
var color = new CvScalar(0, 0, 255);
//开始遍历
while (contour != null)
{
//得到这个连通区域的外接矩形
var rect = Cv.BoundingRect(contour);
//如果高度不足，或者长宽比太小，认为是无效数据，否则把矩形画到原图上
if (rect.Height > 10 && (rect.Width * 1.0 / rect.Height) > 0.2)
{
Cv.DrawRect(src, rect, color);
}
//取下一个连通域
contour = contour.HNext;
}
Cv.ReleaseMemStorage(storage);
//显示
Cv.ShowImage("Result", src);
Cv.WaitKey();
Cv.DestroyAllWindows();
}
public void Test()
{
var faceSearcher = new FaceSearchWrapper.FaceSearch();
int count = 0;
var timer = new System.Diagnostics.Stopwatch();
timer.Start();
foreach (var file in System.IO.Directory.EnumerateFiles(@"G:\pic", "*.jpg"))
{
var img = IplImage.FromFile(file);
var rect = new CvRect(0, 0, img.Width, img.Height);
var faces = faceSearcher.SearchFace(img, rect);
System.Diagnostics.Debug.WriteLine(faces.Length);
count++;
}
var msPerPic = timer.ElapsedMilliseconds / count;
System.Diagnostics.Debug.WriteLine("millisecond per picture: " + msPerPic);
}
public static IplImage GetImage2()
{
return(IplImage.FromFile("2.jpg"));
}
private double CalculateHistogramDistance(string jpg_path1, string jpg_path2)
{
int i, sch = 0;
float[] range_0 = { 0, 256 };
float[][] ranges = { range_0 };
double tmp, dist = 0;
IplImage src_img1, src_img2;
IplImage[] dst_img1 = new IplImage[4];
IplImage[] dst_img2 = new IplImage[4];
CvHistogram[] hist1 = new CvHistogram[4];
CvHistogram hist2;
src_img1 = IplImage.FromFile(jpg_path1, LoadMode.AnyDepth | LoadMode.AnyColor);
// チャンネル数分の画像領域を確保
sch = src_img1.NChannels;
for (i = 0; i < sch; i++)
{
dst_img1[i] = Cv.CreateImage(Cv.Size(src_img1.Width, src_img1.Height), src_img1.Depth, 1);
}
// ヒストグラム構造体を確保
int[] nHisSize = new int[1];
nHisSize[0] = 256;
hist1[0] = Cv.CreateHist(nHisSize, HistogramFormat.Array, ranges, true);
// 入力画像がマルチチャンネルの場合，画像をチャンネル毎に分割
if (sch == 1)
{
Cv.Copy(src_img1, dst_img1[0]);
}
else
{
Cv.Split(src_img1, dst_img1[0], dst_img1[1], dst_img1[2], dst_img1[3]);
}
for (i = 0; i < sch; i++)
{
Cv.CalcHist(dst_img1[i], hist1[i], false);
Cv.NormalizeHist(hist1[i], 10000);
if (i < 3)
{
Cv.CopyHist(hist1[i], ref hist1[i + 1]);
}
}
Cv.ReleaseImage(src_img1);
src_img2 = IplImage.FromFile(jpg_path2, LoadMode.AnyDepth | LoadMode.AnyColor);
// 入力画像のチャンネル数分の画像領域を確保
for (i = 0; i < sch; i++)
{
dst_img2[i] = Cv.CreateImage(Cv.Size(src_img2.Width, src_img2.Height), src_img2.Depth, 1);
}
// ヒストグラム構造体を確保
nHisSize[0] = 256;
hist2 = Cv.CreateHist(nHisSize, HistogramFormat.Array, ranges, true);
// 入力画像がマルチチャンネルの場合，画像をチャンネル毎に分割
if (sch == 1)
{
Cv.Copy(src_img2, dst_img2[0]);
}
else
{
Cv.Split(src_img2, dst_img2[0], dst_img2[1], dst_img2[2], dst_img2[3]);
}
try
{
dist = 0.0;
// ヒストグラムを計算，正規化して，距離を求める
for (i = 0; i < sch; i++)
{
Cv.CalcHist(dst_img2[i], hist2, false);
Cv.NormalizeHist(hist2, 10000);
tmp = Cv.CompareHist(hist1[i], hist2, HistogramComparison.Bhattacharyya);
dist += tmp * tmp;
}
dist = Math.Sqrt(dist);
Cv.ReleaseHist(hist2);
Cv.ReleaseImage(src_img2);
}
catch (OpenCVException ex)
{
Console.WriteLine("Error : " + ex.Message);
}
return(dist);
}
public static IplImage LoadIntoIpl(this string path)
{
return(IplImage.FromFile(path));
}
static void Main(string[] args)
{
CvCapture videoCaprure = null;
try
{
videoCaprure = CvCapture.FromFile(FILE_NAME);
}
catch (Exception e)
{
Console.WriteLine("Unable to open file {0}", FILE_NAME);
Console.WriteLine(e.ToString());
Console.ReadKey();
}
Cv.NamedWindow(MAIN_WINDOW_NAME, WindowMode.AutoSize);
double rate = videoCaprure.GetCaptureProperty(CvConst.CV_CAP_PROP_FPS);
int delay = (int)(1000 / rate);
//int counter = 0;
IplImage backgroundImage = IplImage.FromFile(BACKDROUND_IMAGE_FILE_NAME);
IplImage grayBackgroundImage = Cv.CreateImage(backgroundImage.Size, backgroundImage.Depth, 1);
Cv.CvtColor(backgroundImage, grayBackgroundImage, ColorConversion.RgbToGray);
Console.WriteLine("NChannels = " + backgroundImage.NChannels);
Console.ReadKey();
//IplImage grayBackgroundImage = Cv.CreateImage(backgroundImage.Size, backgroundImage.Depth, 1);
//Cv.CvtColor(backgroundImage, grayBackgroundImage, ColorConversion.RgbToGray););
while (true)
{
var currentOgirinalFrame = videoCaprure.QueryFrame();
if (currentOgirinalFrame == null)
{
return;
}
//counter++;
//if (counter % 3 != 0)
// continue;
IplImage grayOriginalFrame = Cv.CreateImage(currentOgirinalFrame.Size, currentOgirinalFrame.Depth, 1);
Cv.CvtColor(currentOgirinalFrame, grayOriginalFrame, ColorConversion.RgbToGray);
IplImage differenceBetweenFrames = Cv.CreateImage(grayOriginalFrame.Size, grayOriginalFrame.Depth, 1);
Cv.AbsDiff(grayOriginalFrame, grayBackgroundImage, differenceBetweenFrames);
//Cv.Smooth(differenceBetweenFrames, differenceBetweenFrames, SmoothType.Blur);
//IplImage graydifferenceBetweenFrames = Cv.CreateImage(differenceBetweenFrames.Size, differenceBetweenFrames.Depth, 1);
//Cv.CvtColor(differenceBetweenFrames, graydifferenceBetweenFrames, ColorConversion.RgbToGray);
//Cv.ShowImage("differenceBetweenFrames", differenceBetweenFrames);
Cv.Threshold(differenceBetweenFrames, differenceBetweenFrames, 50, 255, ThresholdType.Binary);
Cv.Erode(differenceBetweenFrames, differenceBetweenFrames);
//finding blobs
CvBlobs blobs = new CvBlobs(differenceBetweenFrames);
blobs.FilterByArea(300, 10000);
//blobs.Label(differenceBetweenFrames);
var currentFrameWithRedRects = Cv.CreateImage(currentOgirinalFrame.Size, currentOgirinalFrame.Depth, currentOgirinalFrame.NChannels);
currentOgirinalFrame.Copy(currentFrameWithRedRects);
foreach (var cvBlob in blobs)
{
Cv.Rectangle(currentFrameWithRedRects, cvBlob.Value.Rect, CvColor.Red, 4);
}
Console.WriteLine(blobs.Count);
Cv.ShowImage(MAIN_WINDOW_NAME, currentFrameWithRedRects);
Cv.ShowImage("Result", differenceBetweenFrames);
//Cv.ShowImage("backgroundImage", backgroundImage);
Cv.WaitKey(delay);
//currentOgirinalFrame.Copy(differenceBetweenFrames);
}
}